Managing agile software deployment for cloud infrastructure can be challenging. Deployments should be automated whenever possible to ensure consistent version management. Nevertheless, it can happen that identical software versions are not deployed to all servers. Such imperfect version management is a potential time-bomb. Distributed systems and microservices often rely on the deployment of the exact same software version installed on every cluster node.

The Grafana community comes up with some pretty cool stuff, and we’re hoping to spotlight some of it from time to time. Today, we’re starting with the BigQuery datasource plugin developed by the team at DoiT International. DoiT is a reseller of Google Cloud and AWS that helps companies either move from on premise to cloud or move from one cloud provider to another.

One of the common pieces of advice I hear given to managed service providers (MSPs) is to “go narrow”—find a niche and become a specialist. This is generally sound advice. Specialization typically means your MSP faces less competition and becomes much easier to find in an otherwise crowded marketplace. But finding an area to specialize in is easier said than done. So how do you find a great niche for your MSP?

The world of log management is ridden with woes because most solutions are based on a classical database technology: the index. Indexing has been an accepted and useful approach to collecting and analyzing log data for well over a decade. But its time has passed. Based on index-free architectures, modern log management systems like Humio, Loki, and Scalyr provide faster service at a much lower cost.

At this point in our series, you’re likely quite familiar with the many opportunities and challenges that Kubernetes presents (especially when it comes to monitoring!). The last couple of posts take at a look at Prometheus for monitoring Kubernetes, with a side-by-side comparison with Sensu, and illustrate how they work in tandem.

LogicMonitor is proud to announce anomaly visualization as an addition to our growing AIOps capabilities! With this new functionality, users are able to visualize anomalies that occur for a monitored resource and compare that anomaly to key historical signals, such as the past 24hrs, 7 days, or 30 days. Anomaly visualization complements LogicMonitor’s existing forecasting functionality and provides another layer of intelligence to better understand resource health.

We are halfway through 2019 and with the third release of the year, our momentum remains strong as we continue to deliver significant product innovations for our customers across the Qlik portfolio.